4.5 Article

Detection of High-Sensitivity Troponin in Outpatients With Stable Pulmonary Hypertension Identifies a Subgroup at Higher Risk of Adverse Outcomes

Journal

JOURNAL OF CARDIAC FAILURE
Volume 20, Issue 1, Pages 31-37

Publisher

CHURCHILL LIVINGSTONE INC MEDICAL PUBLISHERS
DOI: 10.1016/j.cardfail.2013.12.001

Keywords

Risk prediction models; prognosis; B-type natriuretic peptide; neutrophil gelatinase-associated lipocalin

Funding

  1. Irish Heart Foundation
  2. University College Dublin

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Background: The detection of elevations in cardiorenal biomarkers, such as troponins, B-type natriuretic peptides (BNPs), and neutrophil gelatinase-associated lipocalins, are associated with poor outcomes in patients hospitalized with acute heart failure. Less is known about the association of these markers with adverse events in chronic right ventricular dysfunction due to pulmonary hypertension, or whether their measurement may improve risk assessment in the outpatient setting. Methods and Results: We performed a cohort study of 108 patients attending the National Pulmonary Hypertension Unit in Dublin, Ireland, from 2007 to 2009. Cox proportional hazards analysis and receiver operating characteristic curves were used to determine predictors of mortality and hospitalization. Death or hospitalization occurred in 50 patients (46.3%) during the median study period of 4.1 years. Independent predictors of mortality were: 1) decreasing 6-minute walk test (6MWT; hazard ratio [HR] 12.8; P < .001); 2) BNP (HR 6.68; P < .001); and 3) highly sensitive troponin (hsTnT; HR 5.48; P < .001). Adjusted hazard analyses remained significant when hsTnT was added to a model with BNP and 6MWT (HR 9.26, 95% CI 3.61-23.79), as did the predictive ability of the model for death and rehospitalization (area under the receiver operating characteristic curve 0.81, 95% CI 0.73-0.90). Conclusions: Detection of troponin using a highly sensitive assay identifies a pulmonary hypertension subgroup with a poorer prognosis. hsTnT may also be used in a risk prediction model to identify patients at higher risk who may require escalation of targeted pulmonary vasodilator therapies and closer clinical surveillance.

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